Type I and Ir pleuropulmonary blastoma (PPB): A report from the International PPB/DICER1 Registry.

BACKGROUND: Pleuropulmonary blastoma (PPB) is the most common lung cancer of infancy and early childhood. Type I PPB is a purely cystic lesion that has a microscopic population of primitive small cells with or without rhabdomyoblastic features and may progress to type II or III PPB, whereas type Ir lacks primitive small cells. METHODS: Children with suspected PPB were enrolled in the International PPB/DICER1 Registry. Pathology was centrally reviewed, and follow-up was ascertained annually. RESULTS: Between 2006 and 2022, 205 children had centrally reviewed type I or Ir PPB; 39% of children with type I and 5% of children with type Ir PPB received chemotherapy. Outcomes were favorable, although 11 children (nine with type I and two with type Ir PPB) experienced progression to type II/III (n = 8) or regrowth of type I PPB at the surgical site (n = 3), none of whom received chemotherapy before progression. Age and cyst size in combination were more suitable than either factor alone in predicting whether a particular lesion was type I or Ir PPB. CONCLUSIONS: For young children with type I PPB, outcomes are favorable, but complete resection is indicated because of the risk for progression. Chemotherapy may be useful in a subset of children at increased risk for recurrence/progression. Efforts to risk stratify children with type I PPB to optimize outcomes while reducing treatment-related side effects are underway.

Rapid equilibrium dialysis, ultrafiltration or ultracentrifugation? Evaluation of methods to quantify the unbound fraction of substances in plasma.

In pharmacokinetics plasma protein binding (PPB) is a well-established parameter impacting drug disposition. The unbound fraction (fu) is arguably regarded the effective concentration at the target site. Pharmacology and toxicology, increasingly use in vitro models. The translation of in vitro concentrations to in vivo doses can be supported by toxicokinetic modelling, e.g. physiologically based toxicokinetic models (PBTK). PPB of a test substance is an input parameter for PBTK. We compared three methods to quantify fu: rapid equilibrium dialysis (RED), ultrafiltration (UF) and ultracentrifugation (UC) using twelve substances covering a wide range of Log Pow (-0.1 to 6.8) and molecular weights (151 and 531 g/mol): Acetaminophen, Bisphenol A, Caffeine, Colchicine, Fenarimol, Flutamide, Genistein, Ketoconazole, α-Methyltestosterone, Tamoxifen, Trenbolone and Warfarin. After RED and UF separation, three polar substances (Log Pow < 2) were largely unbound (fu > 70%), while more lipophilic substances were largely bound (fu < 33%). Compared to RED or UF, UC resulted in a generally higher fu of lipophilic substances. fu obtained after RED and UF were more consistent with published data. For half of the substances, UC resulted in fu higher than the reference data. UF, RED and both UF and UC, resulted in lower fu of Flutamide, Ketoconazole and Colchicine, respectively. For fu quantifications, the separation method should be selected according to the test substance's properties. Based on our data, RED is suitable for a broader range of substances while UC and UF are suitable for polar substances.

Assessing the role of positron emission tomography and bone scintigraphy in imaging of pleuropulmonary blastoma (PPB): A report from the International PPB/DICER1 Registry.

BACKGROUND: Pleuropulmonary blastoma (PPB) is the most common primary lung neoplasm of infancy and early childhood. Given the rarity of PPB, the role of positron emission tomography (PET) and bone scintigraphy (bone scans) in diagnostic evaluation and surveillance has not been documented to date. Available PET and bone scan data are presented in this study. PROCEDURES: Patients with PPB enrolled in the International PPB/DICER1 Registry and available PET imaging and/or bone scan reports were retrospectively abstracted. RESULTS: On retrospective analysis, 133 patients with type II and III (advanced) PPB were identified with available report(s) (PET scan only = 34, bone scan only = 83, and both bone scan and PET = 16). All advanced primary PPB (n = 11) and recurrent (n = 8) tumors prior to treatment presented with 18 F-fluorodeoxyglucose (FDG)-avid lesions, with median maximum standardized uptake values of 7.4 and 6.7, respectively. False positive FDG uptake in the thorax was noted during surveillance (specificity: 59%). Bone metastases were FDG-avid prior to treatment. Central nervous system metastases were not discernable on PET imaging. Sensitivity and specificity of bone scans for metastatic bone disease were 89% and 92%, respectively. Bone scans had a negative predictive value of 99%, although positive predictive value was 53%. Four patients with distant bone metastases had concordant true positive bone scan and PET. CONCLUSION: Primary, recurrent, and/or extracranial metastatic PPB presents with an FDG-avid lesion on PET imaging. Additional prospective studies are needed to fully assess the utility of nuclear medicine imaging in surveillance for patients with advanced PPB.

Inertial Sensor-Based Sport Activity Advisory System Using Machine Learning Algorithms.

The aim of this study was to develop a physical activity advisory system supporting the correct implementation of sport exercises using inertial sensors and machine learning algorithms. Specifically, three mobile sensors (tags), six stationary anchors and a system-controlling server (gateway) were employed for 15 scenarios of the series of subsequent activities, namely squats, pull-ups and dips. The proposed solution consists of two modules: an activity recognition module (ARM) and a repetition-counting module (RCM). The former is responsible for extracting the series of subsequent activities (so-called scenario), and the latter determines the number of repetitions of a given activity in a single series. Data used in this study contained 488 three defined sport activity occurrences. Data processing was conducted to enhance performance, including an overlapping and non-overlapping window, raw and normalized data, a convolutional neural network (CNN) with an additional post-processing block (PPB) and repetition counting. The developed system achieved satisfactory accuracy: CNN + PPB: non-overlapping window and raw data, 0.88; non-overlapping window and normalized data, 0.78; overlapping window and raw data, 0.92; overlapping window and normalized data, 0.87. For repetition counting, the achieved accuracies were 0.93 and 0.97 within an error of ±1 and ±2 repetitions, respectively. The archived results indicate that the proposed system could be a helpful tool to support the correct implementation of sport exercises and could be successfully implemented in further work in the form of web application detecting the user's sport activity.

H2S/Butane Dual Gas Sensing Based on a Hydrothermally Synthesized MXene Ti3C2Tx/NiCo2O4 Nanocomposite.

Real-time sensing of hydrogen sulfide (H2S) at room temperature is important to ensure the safety of humans and the environment. Four kinds of different nanocomposites, such as MXene Ti3C2Tx, Ti3AlC2, WS2, and MoSe2/NiCo2O4, were synthesized using the hydrothermal method in this paper. Initially, the intrinsic properties of the synthesized nanocomposites were studied using different techniques. P-type butane and H2S-sensing behaviors of nanocomposites were performed and analyzed deeply. Four sensor sheets were fabricated using a spin-coating method. The gas sensor was distinctly part of the chemiresistor class. The MXene Ti3C2Tx/NiCo2O4-based gas sensor detected the highest response (16) toward 10 ppm H2S at room temperature. In comparison, the sensor detected the highest response (9.8) toward 4000 ppm butane at 90 °C compared with the other three fabricated sensors (Ti3AlC2, WS2, and MoSe2/NiCo2O4). The MXene Ti3C2Tx/NiCo2O4 sensor showed excellent responses, minimum limits of detection (0.1 ppm H2S and 5 ppm butane), long-term stability, and good reproducibility compared with the other fabricated sensors. The highest sensing properties toward H2S and butane were accredited to p-p heterojunctions, higher BET surface areas, increased oxygen species, etc. These simply synthesized nanocomposites and fabricated sensors present a novel method for tracing H2S and butane at the lowest concentration to prevent different gas-exposure-related diseases.

Roseomonas rosulenta sp. nov., isolated from rice paddy soil.

Three bacterial isolates, Gram-stain-negative, non-motile, coccobacilli-shaped bacteria, strains OP-27T, OP-5 and OP-30, were isolated from rice paddy soil. Phylogenetic analyses based on 16S rRNA gene sequences revealed that three isolates belonged to the genus Roseomonas, showing the highest sequence similarities to Roseomonas sediminicola FW-3T (98.1%) and Roseomonas lacus TH-G33T (98.0%). The genome size of strain OP-27T was 5.2 Mb in a single contig with DNA G+C content of 71.2%. The genome included 5164 predicted protein-coding genes, as well as 48 tRNA, 4 rRNA and 4 mRNA genes. The average nucleotide identity value between strain OP-27T and type strains of related species of the genus Roseomonas were 81.1-83.1%, and the digital DNA-DNA hybridization values of strain OP-27T and the related strains were 24.6-26.8%, respectively. The DNA-DNA hybridization values between strains OP-27T, OP-5 and OP-30 were 84-100% and its closest relative, Roseomonas sediminicola KACC 16616T was 21.1%. The major fatty acids were C18:1 ω7c, C18:1 2-OH and C16:0 and predominant quinone was Q-10. Based on its distinctive phenotypic, phylogenetic, and chemotaxonomic characteristics, the three strains are considered to represent novel species of the genus Roseomonas, for which the name Roseomonas rosulenta sp. nov. is proposed. The type strain is OP-27T (=KACC 21501T= NBRC 114497T).

Effect of Ultraviolet Activation on Sub-ppm NO2 Sensing Dynamics of Poly(3-hexylthiophene)-Bearing Graft Copolymers.

Nitrogen dioxide (NO2) sensors utilising graft copolymers bearing poly(3-hexylthiophene) chains have been developed and investigated in terms of their operation parameters using different carrier gases (N2 or air) and in either dark conditions or with ultraviolet (UV) irradiation. Interestingly, sensor performance improved upon transition from N2 to air, with the inverse being true for most NO2 sensors. UV irradiation both improved sensor dynamics and stabilised the sensor electrical baseline, allowing sensors based on SilPEG to fulfil the requirements of sensing solutions used in industry (below 10% baseline drift after sensors reach saturation) and making them promising candidates for further development and applications. Based on conducted multi-variate experiments, an initial mechanism underlying the interplay of exposure to oxygen (present in air) and UV irradiation was postulated.

Hybrid Carbon Nanotubes/Gold Nanoparticles Composites for Trace Nitric Oxide Detection over a Wide Range of Humidity.

Composites of functionalized single walled carbon nanotubes (SWCNTs) and gold nanoparticles (Au NPs) of ≈15 nm diameter were drop-cast on a printed circuit board (PCB) substrate equipped with interdigitated electrodes to make a hybrid thin film. Addition of Au NPs decorated the surface of SWCNTs networked films and acted as catalysts which resulted into an enhanced sensitivity and low ppb concentration detection limit. The compositions of the film were characterized by scanning electron microscope (SEM). SWCNTs clusters were loaded with various amount of Au NPs ranging from 1-10% (by weight) and their effect on Nitric oxide (NO) sensitivity was studied and optimized. Further, the optimized composite films were tested in both air and nitrogen environments and as well as over a wide relative humidity range (0-97%). Sensors were also tested for the selectivity by exposing to various gases such as nitrous oxide, ammonia, carbon monoxide, sulfur dioxide and acetone. Sensitivity to NO was found much higher than the other tested gases. The advantage of this sensor is that it is sensitive to NO at low ppb level (10 ppb) with estimated response time within 10 s and recovery time around 1 min, and has excellent reproducibility from sensor to sensor and works within the wide range of relative humidity (0-97%).

Prophylactic Clipping After Colorectal Endoscopic Resection Prevents Bleeding of Large, Proximal Polyps: Meta-analysis of Randomized Trials.

BACKGROUND & AIMS: The benefits of prophylactic clipping to prevent bleeding after polypectomy are unclear. We conducted an updated meta-analysis of randomized trials to assess the efficacy of clipping in preventing bleeding after polypectomy, overall and according to polyp size and location. METHODS: We searched the MEDLINE/PubMed, Embase, and Scopus databases for randomized trials that compared the effects of clipping vs not clipping to prevent bleeding after polypectomy. We performed a random-effects meta-analysis to generate pooled relative risks (RRs) with 95% CIs. Multilevel random-effects metaregression analysis was used to combine data on bleeding after polypectomy and estimate associations between rates of bleeding and polyp characteristics. RESULTS: We analyzed data from 9 trials, comprising 71897 colorectal lesions (22.5% 20 mm or larger; 49.2% with proximal location). Clipping, compared with no clipping, did not significantly reduce the overall risk of postpolypectomy bleeding (2.2% with clipping vs 3.3% with no clipping; RR, 0.69; 95% confidence interval [CI], 0.45-1.08; P = .072). Clipping significantly reduced risk of bleeding after removal of polyps that were 20 mm or larger (4.3% had bleeding after clipping vs 7.6% had bleeding with no clipping; RR, 0.51; 95% CI, 0.33-0.78; P = .020) or that were in a proximal location (3.0% had bleeding after clipping vs 6.2% had bleeding with no clipping; RR, 0.53; 95% CI, 0.35-0.81; P < .001). In multilevel metaregression analysis that adjusted for polyp size and location, prophylactic clipping was significantly associated with reduced risk of bleeding after removal of large proximal polyps (RR, 0.37; 95% CI, 0.22-0.61; P = .021) but not small proximal lesions (RR, 0.88; 95% CI, 0.48-1.62; P = .581). CONCLUSIONS: In a meta-analysis of randomized trials, we found that routine use of prophylactic clipping does not reduce risk of postpolypectomy bleeding overall. However, clipping appeared to reduce bleeding after removal of large (more than 20 mm) proximal lesions.

The Effect of Gross Total Resection on Patients with Pleuropulmonary Blastoma.

BACKGROUND: Pleuropulmonary blastoma (PPB) is the most common primary lung cancer in children. While rare, these tumors are highly aggressive. Tumor recurrence and overall survival are dependent on histologic grade and extent of surgical resection. We sought to examine our institutional experience with PPB to determine the effect of gross total resection (GTR) on recurrence and patient outcomes. MATERIALS AND METHODS: After IRB approval, a retrospective chart review from 1998 to 2018 was performed. Cases were confirmed by histology and Dehner Grade (I to III). Data collection included demographics, treatment, extent of surgical resection, and patient outcomes. RESULTS: Eight patients with nine procedures were identified. Histologically, three cases were type 1, 2 type 2, and four poor prognosis type 3. Three patients received neoadjuvant chemotherapy to facilitate surgical resection. The operative goal was to achieve GTR (>95%), and to this end, three partial lobectomies, five lobectomies, and one pneumonectomy were performed. All nine cases achieved GTR, of which eight had negative microscopic margins. Two patients with type III disease recurred (one locally, one distant) and died. One type 3 patient had a positive microscopic hilar margin not amenable to further resection. The patient recurred (distant) but is in remission. With respect to patient outcomes, the event-free survival was 2.3 y with an overall survival of 3.3 y. CONCLUSIONS: From our experience, GTR of PPB is associated with minimal surgical morbidity and good overall survival. Multi-institutional studies are needed to determine if positive surgical margins affect outcomes given the morbidity of mediastinal dissection.

Calculating safety margins using total plasma concentration versus unbound plasma concentration - does it make a difference?

Safety margin, a key aspect of any non-clinical toxicity studies, is calculated by dividing the systemic exposure (AUC) at NOAEL (No Adverse Effect Level) in toxicity studies by the clinical exposure. The validity of using total plasma concentration (Cp) to calculate AUC is often discussed, as it is the unbound plasma concentration (Cup) that elicits the pharmacological and toxicological effects. Data regarding plasma protein binding across species was collected for 114 MSD small molecule compounds which had been discontinued from development either due to non-clinical toxicity or due to clinical Adverse Effects. A >3-fold difference in unbound fraction in plasma (fup) was selected as a meaningful difference in plasma protein binding between non-clinical species and humans. In rats, dogs and non-human primates, approximately 3-5% of the compounds had a >3-fold difference in plasma protein binding than humans. Following assessment of toxicity profile of these compounds, it was concluded that calculation of safety margins after incorporating fup would have still led to the discontinuation of these compounds. Therefore, although fup can still be used for calculation of safety margin on a case by case basis, the routine use of fup for calculation of safety margins is not warranted.

A Highly Sensitive and Selective ppb-Level Acetone Sensor Based on a Pt-Doped 3D Porous SnO2 Hierarchical Structure.

In view of the low sensitivity, high operating temperature and poor selectivity of acetone measurements, in this paper much effort has been paid to improve the performance of acetone sensors from three aspects: increasing the surface area of the material, improving the surface activity and enhancing gas diffusion. A hierarchical flower-like Pt-doped (1 wt %) 3D porous SnO2 (3DPS) material was synthesized by a one-step hydrothermal method. The micropores of the material were constructed by subsequent annealing. The results of the experiments show that the 3DPS-based sensor's response is strongly dependent on temperature, exhibiting a mountain-like response curve. The maximum sensor sensitivity (Ra/Rg) was found to be as high as 505.7 at a heating temperature of 153 °C and with an exposure to 100 ppm acetone. Additionally, at 153 °C, the sensor still had a response of 2.1 when exposed to 50 ppb acetone gas. The 3DPS-based sensor also has an excellent selectivity for acetone detection. The high sensitivity can be explained by the increase in the specific surface area brought about by the hierarchical flower-like structure, the enhanced surface activity of the noble metal nanoparticles, and the rapid diffusion of free-gas and adsorbed gas molecules caused by the multiple channels of the microporous structure.

Prototype of Nitro Compound Vapor and Trace Detector Based on a Capacitive MIS Sensor.

A prototype of a nitro compound vapor and trace detector, which uses the pyrolysis method and a capacitive gas sensor based on the metal-insulator-semiconductor (MIS) structure type Pd-SiO2-Si, was developed and manufactured. It was experimentally established that the detection limit of trinitrotoluene trace for the detector prototype is 1 × 10-9 g, which corresponds to concentration from 10-11 g/cm3 to 10-12 g/cm3. The prototype had a response time of no more than 30 s. The possibility of further improving the characteristics of the prototype detector by reducing the overall dimensions and increasing the sensitivity of the MIS sensors is shown.

Detection of NO2 Down to One ppb Using Ion-in-Conjugation-Inspired Polymer.

Nitrogen dioxide (NO2 ) emission has severe impact on human health and the ecological environment and effective monitoring of NO2 requires the detection limit (limit of detection) of several parts-per-billion (ppb). All organic semiconductor-based NO2 sensors fail to reach such a level. In this work, using an ion-in-conjugation inspired-polymer (poly(3,3'-diaminobenzidine-squarine, noted as PDBS) as the sensory material, NO2 can be detected as low as 1 ppb, which is the lowest among all reported organic NO2 sensors. In addition, the sensor has high sensitivity, good reversibility, and long-time stability with a period longer than 120 d. Theoretical calculations reveal that PDBS offers unreacted amine and zwitterionic groups, which can offer both the H-bonding and ion-dipole interaction to NO2 . The moderate binding energies (≈0.6 eV) offer high sensitivity, selectivity as well as good reversibility. The results demonstrate that the ion-in-conjugation can be employed to greatly improve sensitivity and selectivity in organic gas sensors by inducing both H-bonding and ion-dipole attraction.

The Response of UV/Blue Light and Ozone Sensing Using Ag-TiO2 Planar Nanocomposite Thin Film.

We successfully fabricated a planar nanocomposite film that uses a composite of silver nanoparticles and titanium dioxide film (Ag-TiO2) for ultraviolet (UV) and blue light detection and application in ozone gas sensor. Ultraviolet-visible spectra revealed that silver nanoparticles have a strong surface plasmon resonance (SPR) effect. A strong redshift of the plasmonic peak when the silver nanoparticles covered the TiO2 thin film was observed. The value of conductivity change for the Ag-TiO2 composite is 4-8 times greater than that of TiO2 film under UV and blue light irradiation. The Ag-TiO2 nanocomposite film successfully sensed 100 ppb ozone. The gas response of the composite film increased by roughly six and four times under UV and blue light irradiation, respectively. We demonstrated that a Ag-TiO2 composite gas sensor can be used with visible light (blue). The planar composite significantly enhances photo catalysis. The composite films have practical application potential for wearable devices.

Hg2+ Optical Fiber Sensor Based on LSPR Generated by Gold Nanoparticles Embedded in LBL Nano-Assembled Coatings.

Mercury is an important contaminant since it is accumulated in the body of living beings, and very small concentrations are very dangerous in the long term. This paper reports the fabrication of a highly sensitive fiber optic sensor using the layer-by-layer nano-assembly technique with gold nanoparticles (AuNPs). The gold nanoparticles were obtained via a water-based synthesis route that use poly acrylic acid (PAA) as stabilizing agent, in the presence of a borane dimethylamine complex (DMAB) as reducing agent, giving PAA-capped AuNPs. The sensing mechanism is based on the alteration of the Localized Surface Plasmon Resonances (LSPR) generated by AuNPs thanks to the strong chemical affinity of metallic mercury towards gold, which lead to amalgam alloys.

Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques.

BACKGROUND: Cyclic peptide-based drug discovery is attracting increasing interest owing to its potential to avoid target protein depletion. In drug discovery, it is important to maintain the biostability of a drug within the proper range. Plasma protein binding (PPB) is the most important index of biostability, and developing a computational method to predict PPB of drug candidate compounds contributes to the acceleration of drug discovery research. PPB prediction of small molecule drug compounds using machine learning has been conducted thus far; however, no study has investigated cyclic peptides because experimental information of cyclic peptides is scarce. RESULTS: First, we adopted sparse modeling and small molecule information to construct a PPB prediction model for cyclic peptides. As cyclic peptide data are limited, applying multidimensional nonlinear models involves concerns regarding overfitting. However, models constructed by sparse modeling can avoid overfitting, offering high generalization performance and interpretability. More than 1000 PPB data of small molecules are available, and we used them to construct a prediction models with two enumeration methods: enumerating lasso solutions (ELS) and forward beam search (FBS). The accuracies of the prediction models constructed by ELS and FBS were equal to or better than those of conventional non-linear models (MAE = 0.167-0.174) on cross-validation of a small molecule compound dataset. Moreover, we showed that the prediction accuracies for cyclic peptides were close to those for small molecule compounds (MAE = 0.194-0.288). Such high accuracy could not be obtained by a simple method of learning from cyclic peptide data directly by lasso regression (MAE = 0.286-0.671) or ridge regression (MAE = 0.244-0.354). CONCLUSION: In this study, we proposed a machine learning techniques that uses low-dimensional sparse modeling to predict the PPB value of cyclic peptides computationally. The low-dimensional sparse model not only exhibits excellent generalization performance but also improves interpretation of the prediction model. This can provide common an noteworthy knowledge for future cyclic peptide drug discovery studies.

Predicting Fraction Unbound in Human Plasma from Chemical Structure: Improved Accuracy in the Low Value Ranges.

Predicting the fraction unbound in plasma provides a good understanding of the pharmacokinetic properties of a drug to assist candidate selection in the early stages of drug discovery. It is also an effective tool to mitigate the risk of late-stage attrition and to optimize further screening. In this study, we built in silico prediction models of fraction unbound in human plasma with freely available software, aiming specifically to improve the accuracy in the low value ranges. We employed several machine learning techniques and built prediction models trained on the largest ever data set of 2738 experimental values. The classification model showed a high true positive rate of 0.826 for the low fraction unbound class on the test set. The strongly biased distribution of the fraction unbound in plasma was mitigated by a logarithmic transformation in the regression model, leading to improved accuracy at lower values. Overall, our models showed better performance than those of previously published methods, including commercial software. Our prediction tool can be used on its own or integrated into other pharmacokinetic modeling systems.

pPB Peptide-Mediated siRNA-Loaded Stable Nucleic Acid Lipid Nanoparticles on Targeting Therapy of Hepatic Fibrosis.

Hepatic fibrosis is a necessary process in the development of liver diseases such as hepatic cirrhosis and its complications, which has become a serious threat to human health. Currently, antifibrotic drug treatment is ineffective, and one reason should be the lack of liver targeting ability. In this report, polypeptide pPB-modified stable nucleic acid lipid nanoparticles (pPB-SNALPs) were prepared to selectively deliver siRNAs against heat shock protein 47 to the liver for targeted therapy of hepatic fibrosis. First, siRNA sequences with high silencing efficiency were screened based on siRNA transfection efficacy. Then, pPB-SNALPs were prepared, which showed a narrow size distribution with a diameter in the range of 110-130 nm and a neutral z-potential of 0 mV. As evidenced by the in vitro and in vivo targeting study, compared with unmodified SNALP, pPB-SNALP showed increased uptake by LX-2 cells and primary hepatic stellate cells (HSC) of mice in vitro and showed increased liver distribution and HSC uptake in vivo. In addition, pPB-SNALP also exhibited an enhanced inhibitory effect on TAA-induced hepatic fibrosis mice with high gp46 mRNA expression in vivo. In summary, our results demonstrated that pPB-SNALP is an effective liver-targeted delivery system. This study could lay a good foundation for the targeted gene therapy of hepatic fibrosis.

Analysis of the Sensing Properties of a Highly Stable and Reproducible Ozone Gas Sensor Based on Amorphous In-Ga-Zn-O Thin Film.

In this study, the sensing properties of an amorphous indium gallium zinc oxide (a-IGZO) thin film at ozone concentrations from 500 to 5 ppm were investigated. The a-IGZO thin film showed very good reproducibility and stability over three test cycles. The ozone concentration of 60-70 ppb also showed a good response. The resistance change (ΔR) and sensitivity (S) were linearly dependent on the ozone concentration. The response time (T90-res), recovery time (T90-rec), and time constant (τ) showed first-order exponential decay with increasing ozone concentration. The resistance-time curve shows that the maximum resistance change rate (dRg/dt) is proportional to the ozone concentration during the adsorption. The results also show that it is better to sense rapidly and stably at a low ozone concentration using a high light intensity. The ozone concentration can be derived from the resistance change, sensitivity, response time, time constant (τ), and first derivative function of resistance. However, the time of the first derivative function of resistance is shorter than other parameters. The results show that a-IGZO thin films and the first-order differentiation method are promising candidates for use as ozone sensors for practical applications.